Predicting insurance demand from risk attitudes

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      <subfield code="a">Predicting insurance demand from risk attitudes</subfield>
      <subfield code="c">Johannes G. Jaspersen, Marc A. Ragin, Justin R. Sydnor</subfield>
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      <subfield code="a">Can measured risk attitudes and associated structural models predict insurance demand? In an experiment (n = 1730), we elicit measures of utility curvature, probability weighting, loss aversion, and preference for certainty and use them to parameterize seventeen common structural models (e.g., expected utility, cumulative prospect theory). Subjects also make 12 insurance choices over different loss probabilities and prices. The insurance choices show coherence and some correlation with various risk-attitude measures. Yet all the structural models predict insurance poorly, often less accurately than random predictions. This is because established structural models predict opposite reactions to probability changes and more sensitivity to prices than people display. Approaches that temper the price responsiveness of structural models show more promise for predicting insurance choices across different conditions.

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      <subfield code="a">Ragin, Marc A,</subfield>
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      <subfield code="a">Sydnor. Justin R.</subfield>
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      <subfield code="g">07/02/2022 Volumen 89 Número 1 - febrero 2022 , p. 63-96</subfield>
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      <subfield code="t">The Journal of risk and insurance</subfield>
      <subfield code="d">Nueva York : The American Risk and Insurance Association, 1964-</subfield>
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